Exploring “biaoqing” Through Clustering: Computational Insights Into Chinese Digital Culture

Abstract

Memes have become a central aspect of online culture, serving as a medium for individuals to express sentiments, humor, and social commentary in creative and accessible ways. They appear in Chinese social media as biǎoqíng (表情), literally meaning “facial expression,” widely utilized and characterized by their incorporation of cultural references, idiomatic expressions, and conveyance of subtle social messages. This thesis will examine current popular biaoqing based on textual and visual content in an effort to understand how biaoqing is used to comment on current events and daily lives, as well as providing a valuable glimpse into the mentality and sentiments of China’s younger generation, who are the primary creators and consumers of biaoqing. The analysis will be performed through image and word clustering methods conducted on memes collected from Weibo (one of the largest social media platforms in China) and fabiaoqing.com, a site with an extensive collection of trending memes sourced from various Chinese social media platforms. Through analyzing clustering results and dataset trends, this research finds that biaoqing reflects the emotional and social realities of China’s younger generations, often shaped by humor, irony, and online subcultures. It serves not only as a form of expression and coping mechanism, but also as a key component of developing digital communication and internet culture.